arXiv subjects

Yulong Liu

Publications and source records attributed to Yulong Liu.

At least 19 recordsLinked to original sources

arXiv2026

Collective Coherent Perfect Absorption in a Synthetic Photon-Phonon Lattice

Coherent perfect absorption (CPA) has emerged as a powerful paradigm for controlling classical and quantum light, and has been demonstrated across a broad range of physical platforms. CPA realized in optomechanics relies on interference between the input field and the mechanically scattered field, but is intrinsically confined to the weak-cooperativity regime, resulting in a narrow absorption bandwidth and the mechanical mode remains thermally occupied. Here, we experimentally demonstrate collective interference-induced CPA in a synthetic photon--phonon lattice. By harnessing cavity-reservoir-mediated interactions among Floquet lattice sites, collective interference shifts the CPA condition deep into the high-cooperativity regime. This enables CPA to coexist with ground-state cooling of the mechanical oscillator, together with a broadened non-Lorentzian absorption lineshape and a singular group-delay response. Our results identify collective interference as a route to quantum-compatible perfect absorption and long-lived quantum storage.

quant-ph↗

arXiv2026

Rotation topological states: theory and material realization

The conventional characterization of topological materials relies on topological invariants calculated from the entire set of occupied bands. However, when a system possesses rotational symmetry, the occupied Hilbert space can be decomposed into multiple subspaces labeled by distinct rotation eigenvalues. We show that this decomposition reveals hidden topological states characterized by a novel $\mathbb{Z}_2^n$ topological invariant, where $n$ is the number of subspaces, while the conventional $\mathbb{Z}_2$ invariant may fail to detect the topology hidden in the rotation subspaces. Remarkably, time-reversal symmetry pairs conjugate rotation eigenvalues and guarantees that the two subspaces have the same $\mathbb{Z}_2$ invariants, making the topology always hidden from the conventional global invariant. We formulate the theory of rotation-subspace topology and demonstrate its material realization in bulk CsCl. Using first-principles calculations and symmetry analysis, we show that bulk CsCl, which is diagnosed as topologically trivial by the conventional approach, features a nontrivial $\mathbb{Z}_2^3$ invariant along the $\Gamma$-R path and a nontrivial $\mathbb{Z}_2^4$ invariant along the $\Gamma$-Z and M-R paths, leading to double Weyl points on the (111) and (001) surfaces, respectively. The subspace $\mathbb{Z}_2^n$ invariant proposed here serves as a necessary refinement for symmetry-protected topological phases and will facilitate the identification of a large class of topological states overlooked by existing diagnostics.

cond-mat.mtrl-sci↗

arXiv2026

Prefix-Safe Bayesian Belief Tracking for LLM Reasoning Reliability:Separating Calibration from Ranking

Long reasoning traces need reliability estimates before final answers are known. We study prefix-conditioned eventual-success estimation, $P(y=1 \mid o_{1:t})$, using prefix-safe observations. Sequential Bayesian Belief Tracking (SBBT) calibrates observation likelihoods and recursively updates a two-state belief, providing a common tracker for scalar scores, text and self-verification markers, hidden clusters, token-pooling probes, and latent-trajectory features. Across generated open-weight traces on MATH-500, GSM8K, AIME 2025, and RIMO-N, probability quality and ranking separate: score-only SBBT often improves Brier, while AUROC gains require structure-aware evidence beyond strong prefix-safe baselines. In the strongest hard math setting, structure-aware observations reach +0.110 AUROC against standard prefix-safe baselines. Under a same-prefix classifier audit, MATH-500 text markers and RIMO-N self-verification signals remain positive. Together, these findings support SBBT as a calibration-aware online inference framework and expose an evidence regime: scalar scores mainly support probability quality, while structure-aware prefix signals support ranking only when strong prefix-safe baselines have not already absorbed the rank evidence.

cs.AI↗

arXiv2026

Dissipative acousto-mechanical parametric interface between high-overtone acoustics and flexural phonons

High-overtone bulk acoustic wave resonators (HBARs) promise advanced phononics, yet achieving nonlinearity remains challenging. We demonstrate a radiation-pressure-type parametric interaction between GHz HBARs and low-frequency flexural modes in a suspended silicon nitride membrane, where mechanical displacement modulates the external dissipation rate to enable dissipative acousto-mechanical coupling. Benefiting from the high quality factor, the system enters the resolved-sideband regime at room temperature, yielding acousto-mechanically induced transparency. We observe tunable Kerr nonlinearity and generate coherent HBAR frequency combs via two-tone driving. Notably, our dissipative coupling strength is 20 times larger than the dispersive coupling, the highest ratio among reported hybrid dissipative-dispersive coupling systems, resulting in the experimental observation of amplification in the reflection spectra under red-sideband driving. The ability to interface dense HBAR modes with a common mechanical resonator provides a scalable on-chip platform for multimode phononic information processing, with quantum phononics potentially achievable at sub-Kelvin temperatures.

quant-ph↗

arXiv2026

Your Simulation Runs but Solves the Wrong Physics: PDE-Grounded Intent Verification for LLM-Generated Multiphysics Simulation Code

Execution-based evaluation of LLM-generated code implicitly treats successful execution as a proxy for correctness. In scientific simulation, this proxy is insufficient: a generated input file can run, mesh, and converge while encoding governing equations that differ from the user's intent. We call this mismatch between intended physics and generated code the comprehension-generation gap. We instantiate this in MOOSE, where Kernel and BC objects map compositionally to weak-form residual terms, enabling deterministic reconstruction of the encoded PDE and comparison against an intended contract. We formalize this comparison as the Intent Fidelity Score (IFS), a structural metric covering governing terms, BCs, ICs, coefficients, and time scheme. Building on IFS, we develop a PDE-grounded refinement loop that uses deterministic violation reports to correct generated code iteratively. We evaluate on MooseBench, a 220-case multiphysics benchmark with PDE-level ground truth released with this work. On this benchmark, our method consistently improves mean IFS over direct generation, with gains concentrated on hard cases. On the subset where direct generation falls below IFS 0.7, refinement adds +0.22 to +0.41 absolute IFS. In the deployment audit, execution-only repair improves execution success while leaving 39-40% of all 220 cases runnable but still solving the wrong physics across the three main deployment-audit models, exposing executability and intent fidelity as separable failure modes. Static proof-of-concept experiments on four PDE-oriented DSLs (UFL/FEniCS, FreeFEM, FiPy, and Devito) suggest that the reconstruction-and-comparison pattern extends beyond MOOSE. These findings reinforce that executable simulation code should be verified against the mathematical structure it is intended to encode, not accepted on execution alone.

cs.LG↗

arXiv2026

Observation of attractor transitions in active magnon-polaritons under microwatt drives

Magnon-polaritons provide a room-temperature platform for investigating nonlinear cavity quantum electrodynamics in the microwave domain, but experimentally observing controlled transitions among distinct nonlinear attractors remains challenging in conventional passive systems, where strong external driving is usually required. Here we report the observation of attractor transitions in an active magnon-polariton formed by a self-oscillating microwave cavity coupled to a yttrium iron garne (YIG) sphere. The feedback loop supplies an internal microwave drive, while Kerr frequency pulling and Suhl-mediated magnon-magnon scattering produce an enhanced effective nonlinearity. Stability analysis using experimentally calibrated parameters reveals a rich fixed-point (FP) landscape with multiple unstable-FP phases and a triple-point region. By tuning gain across these phases, we observe the first experimental evidence of explosive growth of bistability, followed by transitions to multifrequency limit cycles, comb-like/fractal spectra, and broadband chaotic dynamics at microwatt powers. Near a critical point, magnetic-field-triggered switching between nonlinear emission states produces spectral shifts up to 162 times the bare gyromagnetic response. By enabling low-power attractor transitions and attractor-switching-amplified spectral response, active magnon-polaritons open opportunities for nonlinear microwave signal generation, high-precision sensing, and neuromorphic computing.

quant-ph↗

arXiv2026

UniCSG: Unified High-Fidelity Content-Constrained Style-Driven Generation via Staged Semantic and Frequency Disentanglement

Style transfer must match a target style while preserving content semantics. DiT-based diffusion models often suffer from content-style entanglement, leading to reference-content leakage and unstable generation. We present UniCSG, a unified framework for content-constrained, style-driven generation in both text-guided and reference-guided settings. UniCSG employs staged training: (i) a latent-space semantic disentanglement stage that combines low-frequency preprocessing with conditioning corruption to encourage content-style separation, and (ii) a latent-space frequency-aware detail reconstruction stage that refines details via multi-scale frequency supervision. We further incorporate pixel-space reward learning to align latent objectives with perceptual quality after decoding. Experiments demonstrate improved content faithfulness, style alignment, and robustness in both settings.

cs.CV↗

arXiv2026

Aziz and Howl's Gravity-Induced Entanglement Channel is Essentially Classical Mechanics

Aziz and Howl argued that a classical gravitational field can generate quantum entanglement through a quantum-field-theoretic channel mediated by virtual matter propagation. However, their claimed channel is more naturally and accurately understood as semiclassical wavepacket motion in an external gravitational field, rather than as a distinctively quantum-field-theoretic entangling effect. Moreover, the result of their perturbative computation is incorrectly magnified: they selected a discontinuous wavefunction with infinite kinetic energy as the initial state and simultaneously treated it as stationary. Once a correct treatment using Gaussian wavepacket is adapted, the resulting effect will be negligibly small.

quant-ph↗

arXiv2025

Matter-Mediated Entanglement by Classical Gravity under Realistic Matter Dynamics

Gravity-induced entanglement (GIE) is widely regarded as key evidence of nonclassical gravity. Recent work, however, argues that a classical gravitational background can generate entanglement through virtual matter propagation between separated masses. Here we show that this mechanism is negligible once realistic matter dynamics is taken into account. For bound or condensed matter, the binding potential converts the claimed long-range matter-mediated interaction into an exponentially short-ranged one, with an attenuation length of only a few picometers for representative binding energies-well below atomic dimensions and therefore negligible under experimentally relevant distances. For unbound matter, the channel remains negligible before significant wave-packet overlap, while after overlap the packets no longer represent two spatially separated subsystems. Thus the proposed classical matter-mediated mechanism does not challenge the usual interpretation of GIE as evidence for nonclassical gravity once physical localization and finite-time matter dynamics are treated consistently.

quant-ph↗

arXiv2025

Quantum-classical gravity distinction in reservoir-engineered massive quantum system

Massive quantum systems have emerged as compelling tabletop interface-systems for testing the quantum nature of gravity. However, conventional schemes that focus on directly using gravity to induce entanglement suffer from overwhelming environmental decoherence: maintaining entanglement between two oscillators requires an impractically high mechanical quality factor. In this work, we put forward an alternative reservoir-engineered scheme, whose core function is to quantify how gravity modifies (rather than prepares) the steady-state entanglement. Compared to quantum gravity, classical gravity introduces additional dissipative channels, which in turn give rise to distinct entanglement characteristics and thus enable the discrimination between the two types of gravity. Notably, this entanglement difference can still be maintained even when the mechanical quality factor is far below the threshold required by conventional schemes. Moreover, it demonstrates significant robustness against non-gravitational couplings, specifically, those like Casimir and Coulomb forces that are inherent in experimental setups. Our scheme relaxes the experimental requirements for verifying quantum gravity, thereby paving a new path toward its near-term realization.

quant-ph↗

arXiv2025

Cavity Optomechanical Probe of Gravity Between Massive Mechanical Oscillators

Exploring gravitational interactions between objects with small masses has become increasingly timely. Concurrently, oscillators with masses ranging between milligrams and grams in cavity optomechanical systems sparked interest for probing gravity, and even investigating gravity within macroscopic quantum systems. Here we present a measurement scheme for probing gravity in a microwave optomechanical setup that incorporates periodic gravitational modulation between the test mass and the driven source mass at the milligram scale. Optomechanically induced transparency (OMIT) can be utilized to sense the gravitational interactions between test masses and source masses. Specifically, the relative variation in the height of the OMIT peak, expressed as $|1 + re^{iϕ}|^2 - 1$, where $r$ represents the ratio of the amplitude of the gravitational driving force to the radiation pressure force of the probe tone, and $ϕ$ denotes their phase difference, can reach up to 2.3\% under plausible experimental conditions. This work may facilitate cavity-optomechanical probing of gravitational coupling between milligram-scale mechanical oscillators, a mass regime where quantum and gravitational effects converge.

quant-ph↗

arXiv2025

Foundation Cures Personalization: Improving Personalized Models' Prompt Consistency via Hidden Foundation Knowledge

Facial personalization faces challenges to maintain identity fidelity without disrupting the foundation model's prompt consistency. The mainstream personalization models employ identity embedding to integrate identity information within the attention mechanisms. However, our preliminary findings reveal that identity embeddings compromise the effectiveness of other tokens in the prompt, thereby limiting high prompt consistency and attribute-level controllability. Moreover, by deactivating identity embedding, personalization models still demonstrate the underlying foundation models' ability to control facial attributes precisely. It suggests that such foundation models' knowledge can be leveraged to cure the ill-aligned prompt consistency of personalization models. Building upon these insights, we propose FreeCure, a framework that improves the prompt consistency of personalization models with their latent foundation models' knowledge. First, by setting a dual inference paradigm with/without identity embedding, we identify attributes (e.g., hair, accessories, etc.) for enhancements. Second, we introduce a novel foundation-aware self-attention module, coupled with an inversion-based process to bring well-aligned attribute information to the personalization process. Our approach is training-free, and can effectively enhance a wide array of facial attributes; and it can be seamlessly integrated into existing popular personalization models based on both Stable Diffusion and FLUX. FreeCure has consistently shown significant improvements in prompt consistency across these facial personalization models while maintaining the integrity of their original identity fidelity.

cs.CV↗

arXiv2025

Strong coupling between a single-photon and a two-photon Fock state

The realization of strong nonlinear coupling between single photons has been a long-standing goal in quantum optics and quantum information science, promising wide impact applications, such as all-optical deterministic quantum logic and single-photon frequency conversion. Here, we report an experimental observation of the strong coupling between a single-photon and a two-photon Fock state in an ultrastrongly-coupled circuit-QED system. This strong nonlinear interaction is realized by introducing a detuned flux qubit working as an effective coupler between two modes of a superconducting coplanar waveguide resonator. The ultrastrong light--matter interaction breaks the excitation number conservation, and an external flux bias breaks the parity conservation. The combined effect of the two enables the strong one--two-photon coupling. Quantum Rabi-like avoided crossing is resolved when tuning the two-photon resonance frequency of the first mode across the single-photon resonance frequency of the second mode. Within this new photonic regime, we observe the thresholdless second harmonic generation for a mean photon number below one. Our results represent a key step towards a new regime of quantum nonlinear optics, where individual photons can deterministically and coherently interact with each other in the absence of any stimulating fields.

quant-ph↗

arXiv2025

Semantic Voting: A Self-Evaluation-Free Approach for Efficient LLM Self-Improvement on Unverifiable Open-ended Tasks

The rising cost of acquiring supervised data has driven significant interest in self-improvement for large language models (LLMs). Straightforward unsupervised signals like majority voting have proven effective in generating pseudo-labels for verifiable tasks, while their applicability to unverifiable tasks (e.g., translation) is limited by the open-ended character of responses. As a result, self-evaluation mechanisms (e.g., self-judging and entropy minimization) are predominantly used to derive pseudo-labels. However, self-evaluation relying on LLMs typically incurs high computational overhead and introduces overconfidence issues due to intrinsic biases. To address these challenges, we propose a novel self-evaluation-free approach for unverifiable tasks, designed for lightweight yet effective self-improvement. Inspired by majority voting commonly employed in verifiable tasks, we propose semantic voting as a novel mechanism that relaxes the principle of hard matching (i.e., exact matching) toward soft matching (i.e., semantic similarity). Soft matching is achieved by leveraging a lightweight sentence embedding model to quantify semantic similarity, thereby mitigating excessive computational burden and intrinsic bias-associated limitations of self-evaluation. Comprehensive experiments demonstrate that our method achieves substantial gains in computational efficiency and overall better performance than self-evaluation methods across diverse model architectures and tasks.

cs.CL↗

arXiv2025

A Surrogate model for High Temperature Superconducting Magnets to Predict Current Distribution with Neural Network

Finite element methods (FEM) for high-temperature superconducting (HTS) magnets become time-consuming at larger scales, restricting the rapid optimization of meter-scale REBCO solenoids. In this work, a surrogate model based on a fully connected residual neural network (FCRN) is developed to predict the current density distribution in REBCO solenoids. Trained on datasets generated from FEM simulations by the T-A formulation, the FCRN model is evaluated under both fast ramping and steady-state scenarios, showing a lower validation loss than the fully connected network (FCN). When extrapolating geometric parameters beyond the training set, the model achieves a relative error of below 10 % for magnetization losses in Case 1 and an average error of 1.2 % for the central magnetic field in Case 2. Furthermore, deploying the steady-state surrogate model for rapid magnet design found the optimal solution within the parameter space under constraints, with a relative central magnetic field error of 0.2 % compared to FEM results. With rapid predictions, this surrogate model offers an efficient tool for the intelligent design of large-scale HTS magnets.

cs.LG↗

arXiv2025

Optimal Form Factors for Experimental Proposals on Gravity-Induced Entanglement

The interface between quantum mechanics and gravity remains an unresolved issue. Recent advances in precision measurement suggest that detecting gravity-induced entanglement in oscillator systems could provide key evidence for the quantum nature of gravity. However, thermal decoherence imposes strict constraints on system parameters. For entanglement to occur, mechanical frequency $ω_m$, dissipation rate $γ_m$, environmental temperature $T$, oscillator density $ρ$, and the form factor $Λ$-determined by the geometry and arrangement of oscillators-must satisfy a specific constraint. This constraint, intrinsic to the noise model, is considered universal and cannot be improved by quantum control. Given the difficulty in further optimizing $ω_m$, $γ_m$, $ρ$, and $T$, optimizing $Λ$ can relax the constraints on these parameters. In this work, we prove that the form factor has a supremum of $2π$, revealing a fundamental limit of the oscillator system. We propose designs that approach this supremum, nearly an order of magnitude higher than typical spherical oscillators. This optimization could ease experimental constraints and bring quantum gravity validation based on gravity-induced entanglement closer to realization.

quant-ph↗

arXiv2025

Quantize More, Lose Less: Autoregressive Generation from Residually Quantized Speech Representations

Text-to-speech (TTS) synthesis has seen renewed progress under the discrete modeling paradigm. Existing autoregressive approaches often rely on single-codebook representations, which suffer from significant information loss. Even with post-hoc refinement techniques such as flow matching, these methods fail to recover fine-grained details (e.g., prosodic nuances, speaker-specific timbres), especially in challenging scenarios like singing voice or music synthesis. We propose QTTS, a novel TTS framework built upon our new audio codec, QDAC. The core innovation of QDAC lies in its end-to-end training of an ASR-based auto-regressive network with a GAN, which achieves superior semantic feature disentanglement for scalable, near-lossless compression. QTTS models these discrete codes using two innovative strategies: the Hierarchical Parallel architecture, which uses a dual-AR structure to model inter-codebook dependencies for higher-quality synthesis, and the Delay Multihead approach, which employs parallelized prediction with a fixed delay to accelerate inference speed. Our experiments demonstrate that the proposed framework achieves higher synthesis quality and better preserves expressive content compared to baseline. This suggests that scaling up compression via multi-codebook modeling is a promising direction for high-fidelity, general-purpose speech and audio generation.

cs.SD↗

arXiv2025

Experimental and numerical study on current distribution in parallel co-wound no-insulation coils

No-insulation (NI) coils are known for their high thermal stability and self-protection features due to turn-to-turn contacts. Parallel co-winding is a promising method to reduce the charging delay of NI coils while maintaining thermal stability, demonstrating significant potential for applications in fusion and other large-scale or high-field magnets. The non-uniform current distribution among parallel superconducting tapes in parallel co-wound NI coils may lead to thermal and mechanical stability issues. In this work, we conducted current measurement experiments on small parallel co-wound NI REBCO coils to investigate the non-uniform current distribution and its influencing factors. The parallel tapes in the input and output sections of the test coils were separated and a series of Rogowski coils was used to measure the current in each tape during ramping charging process. We combined a field-circuit coupled model based on the T-A formulation with an equivalent circuit model to calculate the current distribution in co-wound coils. Both the measured and calculated results indicated that the current distribution during ramping was highly non-uniform, with some tapes carrying reverse currents. We calculated the current distribution in co-wound coils with different insulation methods and analyzed the influencing factors of the reverse current. The influence of the terminal resistance on current distribution was also discussed. This work could contribute to a deeper understanding of current distribution behavior in co-wound coils and provide insights for their application in large-scale or high-field magnet systems.

physics.app-ph↗